Many computer software applications perform automatic speech recognition (“ASR”) in association with various voice-activated functions. These voice-activated functions may include voice search, short message dictation, voice dialing, call routing, home automation, data entry, speech-to-text processing, and the processing of information queries which may be initiated from any number of devices such as desktop and laptop computers, tablets, smartphones, gaming devices, and automotive computer systems. Various acoustical models are utilized in ASR software to accurately recognize the human voice by minimizing recognition errors. For example, many acoustical models utilize feature minimum phone error rate (“fMPE”), for minimizing recognition errors in speech recognition. Typically, the use of fMPE requires the use of a posterior-based acoustical feature which is characterized by a super vector consisting of the evaluation of posteriors (i.e., the probabilities) to determine where particular speech input frames are located in an acoustic sub-space. However, the evaluation of posteriors may require hundreds of thousands or even millions of Gaussian likelihood evaluations. As a result of the large number of required computations (i.e., high computational costs), the speech recognition process is slowed considerably. It is with respect to these considerations and others that the various embodiments of the present invention have been made.